The dataset contains historical technical data of Dhaka Stock Exchange (DSE). The data was collected from different sources found in the internet where the data was publicly available. The data available here are used for information and research purposes and though to the best of our knowledge, it does not contain any mistakes, there might still be some mistakes. It is not encourages to use this dataset for portfolio management purposes and use this dataset out of your own interest. The contributors do not hold any liability if it is used for any purposes.

Dhaka Stock Exchange Historical Data Overview This dataset contains historical technical data from the Dhaka Stock Exchange (DSE), primarily collected from the official DSE website and supplemented with other publicly available online sources. It is intended solely for informational and research purposes. While every effort has been made to ensure the accuracy and completeness of the data, some inconsistencies or errors may still exist. Users are advised to independently verify any critical information before use. Data Summary: This dataset provides historical trading data for over 700 listed companies on the Dhaka Stock Exchange (DSE), covering the period from January 1999 to April 2025. The dataset consists of 1,684,249 rows and 7 columns, including the following fields: Trading Code: Ticker symbol of the company Date: Trading date Open: Opening price High: Highest price during the day Low: Lowest price during the day Close: Closing price Volume: Total shares traded on that day Notable Findings: The dataset reflects significant market cycles, including bullish and bearish trends, over two decades. Includes major economic events, such as: 2008 global financial crisis impact on DSE The 2010–11 market crash in Bangladesh The effects of COVID-19 (2020–21) on trading volume and volatility Historical price trajectories of major companies like BEXIMCO, SQUARE, GP, BATBC, etc., are well captured. Value of the Data: Offers a comprehensive, time-rich view of Bangladesh’s capital market over 25+ years. Useful for quantitative finance, econometrics, and machine learning applications in time series forecasting. Enables comparative studies across sectors like banking, pharmaceuticals, telecom, textiles, etc. Suitable for academic research, policy analysis, and investment strategy development. Acts as a benchmark dataset for algorithm testing, especially in emerging market scenarios. Potential Use Cases: Financial modeling and stock price forecasting using machine learning Volatility and risk analysis across different timeframes Impact studies of global/regional events on stock performance Development of automated trading systems for the Bangladesh market Training data for university courses in finance, statistics, or data science Backtesting investment strategies and portfolio simulations Data visualization projects to explore long-term market trends